"IIT Madras Launches Foundational AI Models for Indian Languages"
Foundational AI Model
A large-scale AI model trained on broad data, usable as a base for many applications.
Open-weight Model
An AI model whose parameters are publicly released, allowing independent use and fine-tuning.
India is home to hundreds of languages and thousands of dialects. Most AI systems developed globally are trained primarily on English-language data. This creates a structural gap: large sections of India's population cannot access AI-powered services in their own languages. Bridging this gap requires building foundational AI models trained on Indian language data from the ground up, rather than adapting English-centric models.
Natural Language Processing (NLP) is the branch of AI that enables machines to understand, interpret, and generate human language. Key NLP capabilities include speech recognition (converting spoken words to text), speech generation (converting text to spoken words), machine translation (converting text from one language to another), and optical character recognition (OCR) (converting images of printed or handwritten text into machine-readable text). Together, these four capabilities form the core of any multilingual AI system.
India's national AI strategy, articulated through the IndiaAI Mission, emphasises building sovereign AI infrastructure. Sovereign AI refers to AI systems developed, hosted, and governed within a country's own jurisdiction, reducing dependence on foreign technology platforms. Institutions like AI4Bharat at IIT Madras have been at the forefront of this effort, developing open-source datasets and models for Indian languages.
Foundational AI models are large-scale models trained on vast datasets that can serve as a base for many downstream applications. Unlike narrow, task-specific AI tools, foundational models can be adapted for multiple uses without being rebuilt from scratch. In the context of Indian languages, a foundational speech recognition model trained on, say, Tamil or Odia data can be used by an EdTech company, a government department, or a healthcare provider without each of them independently collecting data and training their own model.
The four capabilities launched by Bodhan AI and AI4Bharat address distinct but complementary needs. Speech recognition enables voice-based interfaces, critical for users with low literacy. Speech generation (text-to-speech) allows AI systems to read out information, useful for accessibility and rural outreach. …
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Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?
Which of the following statements with regard to Large Language Models (LLMs) used in machine learning is/are correct?
1.LLMs assign probabilities to the next possible word and then pick the one with the highest probability.
2.LLMs process data through mathematical optimization to minimise prediction errors.
3.LLMs produce unbiased outputs.
Select the answer using the code given below:
Consider the following statements regarding the AI models launched by AI4Bharat and Bodhan AI at IIT Madras for Indian languages:
1.The suite covers four capabilities: speech recognition, speech generation, machine translation, and optical character recognition.
2.The models are released only as closed, proprietary APIs accessible to government institutions.
3.The initiative is supported by the Union Ministry of Education.
Which of the statements given above is/are correct?
Match the following AI capabilities with their correct descriptions:
Capability — Description
1.Speech Recognition — (i) Converts images of printed text into machine-readable digital text
2.Machine Translation — (ii) Converts spoken language into text
3.Optical Character Recognition — (iii) Converts text from one language into another
4.Speech Generation — (iv) Converts text into spoken audio output
Select the correct match:
Which of the following best describes an 'open-weight' AI model release?
Consider the following statements regarding 'sovereign AI infrastructure' as used in the context of India's AI policy:
1.It refers to AI systems developed, hosted, and governed within India's own jurisdiction.
2.It eliminates the need for any international collaboration in AI research.
3.It is intended to reduce dependence on foreign technology platforms for processing citizen data.
Which of the statements given above is/are correct?
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